A Green Neural Network with Privacy Preservation and Interpretability. - De Li; Hongyan Zheng; Zeming Gan; Xianxian Li; Jinyan Wang (TrustCom, 2022)

PGUD: Personalized Graph Universal Defense. - Zeming Gan; Linlin Su; Xianxian Li; Jinyan Wang (ICPADS, 2023)

FINDER: A Simple and Effective Defender against Unnoticeable Graph Injection Attacks. - Linlin Su; Jinyan Wang; Zeming Gan; Xianxian Li (TrustCom, 2023)

Topology-Aware Node Injection Attacks against graph neural networks. - Linlin Su; Jinyan Wang; Zeming Gan; De Li (Neurocomputing, 2025)

D4A: An efficient and effective defense across agnostic adversarial attacks. - Xianxian Li; Zeming Gan; Yan Bai; Linlin Su; De Li; Jinyan Wang (Neural Networks, 2025)

Rethinking the impact of noisy labels in graph classification: A utility and privacy perspective. - De Li; Xianxian Li; Zeming Gan; Qiyu Li; Bin Qu; Jinyan Wang (Neural Networks, 2025)